.. _diophantine-docs: Diophantine =========== Diophantine equations --------------------- The word "Diophantine" comes with the name Diophantus, a mathematician lived in the great city of Alexandria sometime around 250 AD. Often referred to as the "father of Algebra", Diophantus in his famous work "Arithmetica" presented 150 problems that marked the early beginnings of number theory, the field of study about integers and their properties. Diophantine equations play a central and an important part in number theory. We call a "Diophantine equation" to an equation of the form, f(x_1, x_2, \ldots x_n) = 0 where n \geq 2 and x_1, x_2, \ldots x_n are integer variables. If we can find n integers a_1, a_2, \ldots a_n such that x_1 = a_1, x_2 = a_2, \ldots x_n = a_n satisfies the above equation, we say that the equation is solvable. You can read more about Diophantine equations in [1]_ and [2]_. Currently, following five types of Diophantine equations can be solved using :py:meth:~sympy.solvers.diophantine.diophantine and other helper functions of the Diophantine module. - Linear Diophantine equations: a_1x_1 + a_2x_2 + \ldots + a_nx_n = b. - General binary quadratic equation: ax^2 + bxy + cy^2 + dx + ey + f = 0 - Homogeneous ternary quadratic equation: ax^2 + by^2 + cz^2 + dxy + eyz + fzx = 0 - Extended Pythagorean equation: a_{1}x_{1}^2 + a_{2}x_{2}^2 + \ldots + a_{n}x_{n}^2 = a_{n+1}x_{n+1}^2 - General sum of squares: x_{1}^2 + x_{2}^2 + \ldots + x_{n}^2 = k Module structure ---------------- This module contains :py:meth:~sympy.solvers.diophantine.diophantine and helper functions that are needed to solve certain Diophantine equations. It's structured in the following manner. - :py:meth:~sympy.solvers.diophantine.diophantine - :py:meth:~sympy.solvers.diophantine.diop_solve - :py:meth:~sympy.solvers.diophantine.classify_diop - :py:meth:~sympy.solvers.diophantine.diop_linear - :py:meth:~sympy.solvers.diophantine.diop_quadratic - :py:meth:~sympy.solvers.diophantine.diop_ternary_quadratic - :py:meth:~sympy.solvers.diophantine.diop_ternary_quadratic_normal - :py:meth:~sympy.solvers.diophantine.diop_general_pythagorean - :py:meth:~sympy.solvers.diophantine.diop_general_sum_of_squares - :py:meth:~sympy.solvers.diophantine.diop_general_sum_of_even_powers - :py:meth:~sympy.solvers.diophantine.merge_solution When an equation is given to :py:meth:~sympy.solvers.diophantine.diophantine, it factors the equation(if possible) and solves the equation given by each factor by calling :py:meth:~sympy.solvers.diophantine.diop_solve separately. Then all the results are combined using :py:meth:~sympy.solvers.diophantine.merge_solution. :py:meth:~sympy.solvers.diophantine.diop_solve internally uses :py:meth:~sympy.solvers.diophantine.classify_diop to find the type of the equation(and some other details) given to it and then calls the appropriate solver function based on the type returned. For example, if :py:meth:~sympy.solvers.diophantine.classify_diop returned "linear" as the type of the equation, then :py:meth:~sympy.solvers.diophantine.diop_solve calls :py:meth:~sympy.solvers.diophantine.diop_linear to solve the equation. Each of the functions, :py:meth:~sympy.solvers.diophantine.diop_linear, :py:meth:~sympy.solvers.diophantine.diop_quadratic, :py:meth:~sympy.solvers.diophantine.diop_ternary_quadratic, :py:meth:~sympy.solvers.diophantine.diop_general_pythagorean and :py:meth:~sympy.solvers.diophantine.diop_general_sum_of_squares solves a specific type of equations and the type can be easily guessed by it's name. Apart from these functions, there are a considerable number of other functions in the "Diophantine Module" and all of them are listed under User functions and Internal functions. Tutorial -------- First, let's import the highest API of the Diophantine module. >>> from sympy.solvers.diophantine import diophantine Before we start solving the equations, we need to define the variables. >>> from sympy import symbols >>> x, y, z = symbols("x, y, z", integer=True) Let's start by solving the easiest type of Diophantine equations, i.e. linear Diophantine equations. Let's solve 2x + 3y = 5. Note that although we write the equation in the above form, when we input the equation to any of the functions in Diophantine module, it needs to be in the form eq = 0. >>> diophantine(2*x + 3*y - 5) {(3*t_0 - 5, -2*t_0 + 5)} Note that stepping one more level below the highest API, we can solve the very same equation by calling :py:meth:~sympy.solvers.diophantine.diop_solve. >>> from sympy.solvers.diophantine import diop_solve >>> diop_solve(2*x + 3*y - 5) (3*t_0 - 5, -2*t_0 + 5) Note that it returns a tuple rather than a set. :py:meth:~sympy.solvers.diophantine.diophantine always return a set of tuples. But :py:meth:~sympy.solvers.diophantine.diop_solve may return a single tuple or a set of tuples depending on the type of the equation given. We can also solve this equation by calling :py:meth:~sympy.solvers.diophantine.diop_linear, which is what :py:meth:~sympy.solvers.diophantine.diop_solve calls internally. >>> from sympy.solvers.diophantine import diop_linear >>> diop_linear(2*x + 3*y - 5) (3*t_0 - 5, -2*t_0 + 5) If the given equation has no solutions then the outputs will look like below. >>> diophantine(2*x + 4*y - 3) set() >>> diop_solve(2*x + 4*y - 3) (None, None) >>> diop_linear(2*x + 4*y - 3) (None, None) Note that except for the highest level API, in case of no solutions, a tuple of None are returned. Size of the tuple is the same as the number of variables. Also, one can specifically set the parameter to be used in the solutions by passing a customized parameter. Consider the following example: >>> m = symbols("m", integer=True) >>> diop_solve(2*x + 3*y - 5, m) (3*m_0 - 5, -2*m_0 + 5) For linear Diophantine equations, the customized parameter is the prefix used for each free variable in the solution. Consider the following example: >>> diop_solve(2*x + 3*y - 5*z + 7, m) (m_0, m_0 + 5*m_1 - 14, m_0 + 3*m_1 - 7) In the solution above, m_0 and m_1 are independent free variables. Please note that for the moment, users can set the parameter only for linear Diophantine equations and binary quadratic equations. Let's try solving a binary quadratic equation which is an equation with two variables and has a degree of two. Before trying to solve these equations, an idea about various cases associated with the equation would help a lot. Please refer [3]_ and [4]_ for detailed analysis of different cases and the nature of the solutions. Let us define \Delta = b^2 - 4ac w.r.t. the binary quadratic ax^2 + bxy + cy^2 + dx + ey + f = 0. When \Delta < 0, there are either no solutions or only a finite number of solutions. >>> diophantine(x**2 - 4*x*y + 8*y**2 - 3*x + 7*y - 5) {(2, 1), (5, 1)} In the above equation \Delta = (-4)^2 - 4*1*8 = -16 and hence only a finite number of solutions exist. When \Delta = 0 we might have either no solutions or parameterized solutions. >>> diophantine(3*x**2 - 6*x*y + 3*y**2 - 3*x + 7*y - 5) set() >>> diophantine(x**2 - 4*x*y + 4*y**2 - 3*x + 7*y - 5) {(-2*t**2 - 7*t + 10, -t**2 - 3*t + 5)} >>> diophantine(x**2 + 2*x*y + y**2 - 3*x - 3*y) {(t_0, -t_0), (t_0, -t_0 + 3)} The most interesting case is when \Delta > 0 and it is not a perfect square. In this case, the equation has either no solutions or an infinite number of solutions. Consider the below cases where \Delta = 8. >>> diophantine(x**2 - 4*x*y + 2*y**2 - 3*x + 7*y - 5) set() >>> from sympy import sqrt >>> n = symbols("n", integer=True) >>> s = diophantine(x**2 - 2*y**2 - 2*x - 4*y, n) >>> x_1, y_1 = s.pop() >>> x_2, y_2 = s.pop() >>> x_n = -(-2*sqrt(2) + 3)**n/2 + sqrt(2)*(-2*sqrt(2) + 3)**n/2 - sqrt(2)*(2*sqrt(2) + 3)**n/2 - (2*sqrt(2) + 3)**n/2 + 1 >>> x_1 == x_n or x_2 == x_n True >>> y_n = -sqrt(2)*(-2*sqrt(2) + 3)**n/4 + (-2*sqrt(2) + 3)**n/2 + sqrt(2)*(2*sqrt(2) + 3)**n/4 + (2*sqrt(2) + 3)**n/2 - 1 >>> y_1 == y_n or y_2 == y_n True Here n is an integer. Although x_n and y_n may not look like integers, substituting in specific values for n (and simplifying) shows that they are. For example consider the following example where we set n equal to 9. >>> from sympy import simplify >>> simplify(x_n.subs({n: 9})) -9369318 Any binary quadratic of the form ax^2 + bxy + cy^2 + dx + ey + f = 0 can be transformed to an equivalent form X^2 - DY^2 = N. >>> from sympy.solvers.diophantine import find_DN, diop_DN, transformation_to_DN >>> find_DN(x**2 - 3*x*y + y**2 - 7*x + 5*y - 3) (5, 920) So, the above equation is equivalent to the equation X^2 - 5Y^2 = 920 after a linear transformation. If we want to find the linear transformation, we can use :py:meth:~sympy.solvers.diophantine.transformation_to_DN >>> A, B = transformation_to_DN(x**2 - 3*x*y + y**2 - 7*x + 5*y - 3) Here A is a 2 X 2 matrix and B is a 2 X 1 matrix such that the transformation .. math:: \begin{bmatrix} X\\Y \end{bmatrix} = A \begin{bmatrix} x\\y \end{bmatrix} + B gives the equation X^2 -5Y^2 = 920. Values of A and B are as belows. >>> A Matrix([ [1/10, 3/10], [ 0, 1/5]]) >>> B Matrix([ [ 1/5], [-11/5]]) We can solve an equation of the form X^2 - DY^2 = N by passing D and N to :py:meth:~sympy.solvers.diophantine.diop_DN >>> diop_DN(5, 920) [] Unfortunately, our equation has no solution. Now let's turn to homogeneous ternary quadratic equations. These equations are of the form ax^2 + by^2 + cz^2 + dxy + eyz + fzx = 0. These type of equations either have infinitely many solutions or no solutions (except the obvious solution (0, 0, 0)) >>> diophantine(3*x**2 + 4*y**2 - 5*z**2 + 4*x*y + 6*y*z + 7*z*x) {(0, 0, 0)} >>> diophantine(3*x**2 + 4*y**2 - 5*z**2 + 4*x*y - 7*y*z + 7*z*x) {(-16*p**2 + 28*p*q + 20*q**2, 3*p**2 + 38*p*q - 25*q**2, 4*p**2 - 24*p*q + 68*q**2)} If you are only interested in a base solution rather than the parameterized general solution (to be more precise, one of the general solutions), you can use :py:meth:~sympy.solvers.diophantine.diop_ternary_quadratic. >>> from sympy.solvers.diophantine import diop_ternary_quadratic >>> diop_ternary_quadratic(3*x**2 + 4*y**2 - 5*z**2 + 4*x*y - 7*y*z + 7*z*x) (-4, 5, 1) :py:meth:~sympy.solvers.diophantine.diop_ternary_quadratic first converts the given equation to an equivalent equation of the form w^2 = AX^2 + BY^2 and then it uses :py:meth:~sympy.solvers.diophantine.descent to solve the latter equation. You can refer to the docs of :py:meth:~sympy.solvers.diophantine.transformation_to_normal to find more on this. The equation w^2 = AX^2 + BY^2 can be solved more easily by using the Aforementioned :py:meth:~sympy.solvers.diophantine.descent. >>> from sympy.solvers.diophantine import descent >>> descent(3, 1) # solves the equation w**2 = 3*Y**2 + Z**2 (1, 0, 1) Here the solution tuple is in the order (w, Y, Z) The extended Pythagorean equation, a_{1}x_{1}^2 + a_{2}x_{2}^2 + \ldots + a_{n}x_{n}^2 = a_{n+1}x_{n+1}^2 and the general sum of squares equation, x_{1}^2 + x_{2}^2 + \ldots + x_{n}^2 = k can also be solved using the Diophantine module. >>> from sympy.abc import a, b, c, d, e, f >>> diophantine(9*a**2 + 16*b**2 + c**2 + 49*d**2 + 4*e**2 - 25*f**2) {(70*t1**2 + 70*t2**2 + 70*t3**2 + 70*t4**2 - 70*t5**2, 105*t1*t5, 420*t2*t5, 60*t3*t5, 210*t4*t5, 42*t1**2 + 42*t2**2 + 42*t3**2 + 42*t4**2 + 42*t5**2)} function :py:meth:~sympy.solvers.diophantine.diop_general_pythagorean can also be called directly to solve the same equation. Either you can call :py:meth:~sympy.solvers.diophantine.diop_general_pythagorean or use the high level API. For the general sum of squares, this is also true, but one advantage of calling :py:meth:~sympy.solvers.diophantine.diop_general_sum_of_squares is that you can control how many solutions are returned. >>> from sympy.solvers.diophantine import diop_general_sum_of_squares >>> eq = a**2 + b**2 + c**2 + d**2 - 18 >>> diophantine(eq) {(0, 0, 3, 3), (0, 1, 1, 4), (1, 2, 2, 3)} >>> diop_general_sum_of_squares(eq, 2) {(0, 0, 3, 3), (1, 2, 2, 3)} The :py:meth:~sympy.solvers.diophantine.sum_of_squares routine will providean iterator that returns solutions and one may control whether the solutions contain zeros or not (and the solutions not containing zeros are returned first): >>> from sympy.solvers.diophantine import sum_of_squares >>> sos = sum_of_squares(18, 4, zeros=True) >>> next(sos) (1, 2, 2, 3) >>> next(sos) (0, 0, 3, 3) Simple Eqyptian fractions can be found with the Diophantine module, too. For example, here are the ways that one might represent 1/2 as a sum of two unit fractions: >>> from sympy import Eq, S >>> diophantine(Eq(1/x + 1/y, S(1)/2)) {(-2, 1), (1, -2), (3, 6), (4, 4), (6, 3)} To get a more thorough understanding of the Diophantine module, please refer to the following blog. http://thilinaatsympy.wordpress.com/ References ---------- .. [1] Andreescu, Titu. Andrica, Dorin. Cucurezeanu, Ion. An Introduction to Diophantine Equations .. [2] Diophantine Equation, Wolfram Mathworld, [online]. Available: http://mathworld.wolfram.com/DiophantineEquation.html .. [3] Methods to solve Ax^2 + Bxy + Cy^2 + Dx + Ey + F = 0,[online], Available: http://www.alpertron.com.ar/METHODS.HTM .. [4] Solving the equation ax^2+ bxy + cy^2 + dx + ey + f= 0, [online], Available: http://www.jpr2718.org/ax2p.pdf User Functions -------------- This functions is imported into the global namespace with from sympy import *: :func:diophantine ^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.diophantine And this function is imported with from sympy.solvers.diophantine import *: :func:classify_diop ^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.classify_diop Internal Functions ------------------ These functions are intended for internal use in the Diophantine module. :func:diop_solve ^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.diop_solve :func:diop_linear ^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.diop_linear :func:base_solution_linear ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.base_solution_linear :func:diop_quadratic ^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.diop_quadratic :func:diop_DN ^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.diop_DN :func:cornacchia ^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.cornacchia :func:diop_bf_DN ^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.diop_bf_DN :func:transformation_to_DN ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.transformation_to_DN :func:find_DN ^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.find_DN :func:diop_ternary_quadratic ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.diop_ternary_quadratic :func:square_factor ^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.square_factor :func:descent ^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.descent :func:diop_general_pythagorean ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.diop_general_pythagorean :func:diop_general_sum_of_squares ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.diop_general_sum_of_squares :func:diop_general_sum_of_even_powers ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.diop_general_sum_of_even_powers :func:partition ^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.partition :func:sum_of_three_squares ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.sum_of_three_squares :func:sum_of_four_squares ^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.sum_of_four_squares :func:sum_of_powers ^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.sum_of_powers :func:sum_of_squares ^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.sum_of_squares :obj:merge_solution ^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.merge_solution :obj:divisible ^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.divisible :obj:PQa ^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.PQa :obj:equivalent ^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.equivalent :obj:parametrize_ternary_quadratic ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.parametrize_ternary_quadratic :obj:diop_ternary_quadratic_normal ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.diop_ternary_quadratic_normal :obj:ldescent ^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.ldescent :obj:gaussian_reduce ^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.gaussian_reduce :obj:holzer ^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.holzer :obj:prime_as_sum_of_two_squares ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.prime_as_sum_of_two_squares :obj:sqf_normal ^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.sqf_normal :obj:reconstruct ^^^^^^^^^^^^^^^^^^ .. autofunction:: sympy.solvers.diophantine.reconstruct